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29 results for “Sahel”
Adult baobab trees's distribution map across Sahel
<p><span>The baobab tree (<em>Adansonia digitata</em> <em>L.</em>) is an integral part of rural livelihoods throughout the African continent. However, the combined effects of climate change and increasing global demand for baobab products are currently exerting pressure on the sustainable utilization of these resources. Here we employ sub-meter resolution satellite imagery to identify nearly 3</span><span> million baobab trees in the Sahel, a dryland region of 1.5 million km<sup>2</sup>. This achievement is considered an essential step towards improving valuable woody species' management and monitoring system. To prevent mismanagement of this specific tree species, we aggregated every single adult baobab tree map to<span> 5 <span>× </span>5 km grids. We also classified the baobab trees using the tree crown diameters( small: 3-9m; medium 9m-13m; large: >13m). The baobab tree count map is also available for this three different size classes.</span></span></p>
263 MAG annotations for three nested metagenomic studies describe crop-shrub-microbe interactions in an agroecology system in the Sahel
<p>The Sahel region of West Africa is a vulnerable eco-region, where climate change induced drought and a rapidly growing population pose serious threats to food security and contribute to soil degradation. Local and biologically based systems are necessary to maintain crop yields and soil health, and intercropping with native woody shrubs Guiera senegalensis has been discovered as a solution. We have previously shown that soil microbial communities are significantly altered by the presence of shrubs, and that these organisms may have plant growth promoting properties. Here, we augment those data with metagenomic and metatranscriptomic data across three nested experiments: a landscape scale experiment across a rainfall and soil type gradient, a long-term experimental site, and a growth chamber simulated drought experiment. We recovered 263 95% ANI dereplicated metagenome-assembled genomes (MAGs) of medium and high quality to evaluate their relative enrichment and what their encoded metabolisms reveal about mechanisms of microbiome millet support. These data contribute to our understanding of the role of the microbial community crop drought resilience in the Sahel and in semi-arid cropping systems globally. Here we present the DRAM annotations of each MAG, all associated metadata, viral genes and vOTUs from the Optimized Shrub Intercropping Study (OSS), and eukaryotic contigs from the OSS</p>
The Adult Adansonia digitata L. (baobab tree) distribution map derived from very high resolution satelite imagery for 2010s across the Sahel at 1km resolution
<p>The baobab tree (<em>Adansonia digitata</em> <em>L.</em>) is an integral part of rural livelihoods throughout the African continent. However, the combined effects of climate change and increasing global demand for baobab products are currently exerting pressure on the sustainable utilization of these resources. Here we employ sub-meter resolution satellite imagery to identify nearly 3 million baobab trees in the Sahel, a dryland region of 1.5 million km<sup>2</sup>. This achievement is considered an essential step towards improving valuable woody species' management and monitoring system. The map's overall underestimate bias is 0.27. To prevent mismanagement of this specific tree species, we aggregated every single adult baobab tree map to 1 × 1 km grids. We also classified the baobab trees using the tree crown diameters( small: 3-9m; medium 9m-13m; large: >13m). The baobab tree count map is also available for these three different size classes. </p>
Tradeoffs between the use of improved varieties and agrobiodiversity conservation in the Sahel
<p>This folder includes the data source and do-files used for writing the paper entitled "Tradeoffs between the use of improved varieties and agrobiodiversity conservation in the Sahel".</p>
Fig. 2 in Late Cretaceous crest-bearing shrimps from the Sahel Alma Lagerstätte of Lebanon
Fig. 2. Type material of crest−bearing shrimp Palaeobenthesicymus libanensis (Brocchi, 1875) from the Sahel Alma Lagerstätte (upper Santonian, Lebanon). A. Reproduction of Brocchi's (1875) lithography, left lateral view, specimen considered to be definitively lost. B. Complete specimen (MNHN.F.A30593, Arambourg collection), left lateral view, specimen chosen as neotype for P. libanensis (Brocchi, 1875). Photograph (B1) and camera lucida line drawing (B2), note the well−developed rostral crest and the bilobed eyes.
Fig. 9 in Late Cretaceous crest-bearing shrimps from the Sahel Alma Lagerstätte of Lebanon
Fig. 9. Reconstruction of crest−bearing shrimp Palaeobenthesicymus libanensis (Brocchi, 1875). Drawing: Charlène Letenneur (MNHN, scientific draughtsman).
Fig. 1 in Late Cretaceous crest-bearing shrimps from the Sahel Alma Lagerstätte of Lebanon
Fig. 1. Map of Lebanon showing the main fossiliferous localities yielding exceptionally preserved Cenomanian faunas (Hadjoula, Hakel, En Nammoura, Maifouk, Lagerstätten) and Santonian faunas (Sahel Alma Lagerstätte).
Fig. 4 in Late Cretaceous crest-bearing shrimps from the Sahel Alma Lagerstätte of Lebanon
Fig. 4. The crest−bearing shrimp Palaeobenthesicymus libanensis (Brocchi, 1875) from the Sahel Alma Lagerstätte (late Santonian, Lebanon). A. Sub−complete specimen (MNHN.F.A30595), dorsal view (A1) and camera lucida line drawing (A2), note the cephalothoracic grooves, the scaphocerites with white small spheres on the outer margins (epibionts), and the fragment of intestinal canal; grey areas correspond to mineralized soft−tissues. B. Cephalic region of fragmentary specimen (MNHN.F.A30585), ventral view, note the two pairs of antennulae. C. Fragmentary specimen (MNHN.F.SHA.545), left lateral view, cephalic region showing well−preserved antennulae and antennae, note the very pointed distal extremity of the scaphocerite. D. Sub−complete specimen (MNHN.F.A30599), left lateral view, note the eyes and the multiarticulated antennae.
Fig. 6 in Late Cretaceous crest-bearing shrimps from the Sahel Alma Lagerstätte of Lebanon
Fig. 6. The crest−bearing shrimp Palaeobenthesicymus libanensis (Brocchi, 1875) from the Sahel Alma Lagerstätte (late Santonian, Lebanon). A. Male specimen (MNHN.F.A30709), left lateral view (A1), note the petasma, a modified endopodite of the first pleopod in copulatory appendage (black frame). Detailed view of the same petasma composed of unit 1 (two thin elements joined on their distal extremity) and unit 2 (subtriangular scale) (A2). B. Pleon of fragmentary specimen (MNHN.F.A30708), right lateral view, note the well−developed pleopods connected to cylindrical protopodites and the long intestinal canal parallel to the pleonal axis. C. Pleon of sub−complete specimen (MNHN.F.A30602), left lateral view, note the rounded ventral margin of pleurae and the well−marked dorsal ridge on somites 5 and 6. D. Small specimen (MNHN.F.A30596), right lateral view, note the well−preserved tail fan.
Fig. 3 in Late Cretaceous crest-bearing shrimps from the Sahel Alma Lagerstätte of Lebanon
Fig. 3. Anatomical details of the neotype (MNHN.F.A30593, Arambourg collection) of crest−bearing shrimp Palaeobenthesicymus libanensis (Brocchi, 1875) from the Sahel Alma Lagerstätte (upper Santonian, Lebanon). A. Anterior part showing the pair of bilobed eyes and some fragmentary cephalic appendages, note the short rostrum with blunt anterior end. B. Rostral crest, very thin, with a thickened dorsal ridge, note two indentations (black arrows) probably corresponding to small healed wounds. C. Tail fan with well−developed uropods, note the very elongate uropodal exopod bearing a rounded diaeresis (black arrow).
FIG. 2 in Fossil sponge gemmules, epibionts of Carpopenaeus garassinoi n. sp. (Crustacea, Decapoda) from the Sahel Alma Lagerstätte (Late Cretaceous, Lebanon)
FIG. 2. — Sponge gemmules on the rostrum of the shrimp Carpopenaeus garassinoi Charbonnier n. sp. under UV light: A, general view of the shrimp, note the white color of the epibionts; B, general view of the rostrum; C, detail of the proximal part of the rostrum showing isolated gemmules or linked gemmules forming a network. Scale bars: A, 2 cm; B, C, 1 mm.
Assessment of acetochlor use areas in the Sahel region of Western Africa using geospatial methods
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30 Years of Land Cover and Fraction Cover Changes over the Sudano-Sahel using Landsat Timeseries
<p>30m resolution historically consistent land cover and cover fraction maps over the Sudano-Sahel for the period 1986-2015. These land cover / cover fraction maps are achieved based on the Landsat archive preprocessed on Google Earth Engine and a random forest classification / regression model, while historical consistency is achieved using the Hidden Markov Model.</p> <p>Validated land cover / cover fraction maps covering the full Sudano-Sahel are provided for 2015 (2015_Sahel.zip), while historical maps are available for four focus areas. The extent of the areas are displayed in 11_study_area.jpeg</p> <p>Each of the zip files contains 14 GeoTIFF files for the respective period and area:</p> <ul> <li>Landsat_LC30_epochYYYY_AREA_bare-coverfraction-layer.tif [0-100%]</li> <li>Landsat_LC30_epochYYYY_AREA_crops-coverfraction-layer.tif [0-100%]</li> <li>Landsat_LC30_epochYYYY_AREA_DataDensityIndicator.tif [# overpasses that are used as input for the creation of the maps for this region / epoch]</li> <li>Landsat_LC30_epochYYYY_AREA_discrete-classification-HMM.tif [temporally cleaned discrete classification map using the Hidden Markov Model; legend see below] </li> <li>Landsat_LC30_epochYYYY_AREA_discrete-classification.tif [original discrete classification map; legend see below]</li> <li>Landsat_LC30_epochYYYY_AREA_forest-type-layer.tif [legend see below]</li> <li>Landsat_LC30_epochYYYY_AREA_grass-coverfraction-layer.tif [0-100%]</li> <li>Landsat_LC30_epochYYYY_AREA_moss-coverfraction-layer.tif [0-100%]</li> <li>Landsat_LC30_epochYYYY_AREA_shrub-coverfraction-layer.tif [0-100%]</li> <li>Landsat_LC30_epochYYYY_AREA_snow-coverfraction-layer.tif [0-100%]</li> <li>Landsat_LC30_epochYYYY_AREA_tree-coverfraction-layer.tif [0-100%]</li> <li>Landsat_LC30_epochYYYY_AREA_urban-coverfraction-layer.tif [0-100%]</li> <li>Landsat_LC30_epochYYYY_AREA_water-permanent-coverfraction-layer.tif [0-100%]</li> <li>Landsat_LC30_epochYYYY_AREA_water-seasonal-coverfraction-layer.tif [0-100%]</li> </ul> <p>Discrete classification legend:</p> <ul> <li>0: Unknown. No or not enough satellite data available.</li> <li>20: Shrubs. Woody perennial plants with persistent and woody stems and without any defined main stem being less than 5 m tall. The shrub foliage can be either evergreen or deciduous.</li> <li>30: Herbaceous vegetation. Plants without persistent stem or shoots above ground and lacking definite firm structure. Tree and shrub cover is less than 10 %.</li> <li>40: Cultivated and managed vegetation / agriculture. Lands covered with temporary crops followed by harvest and a bare soil period (e.g., single and multiple cropping systems). Note that perennial woody crops will be classified as the appropriate forest or shrub land cover type.</li> <li>50: Urban / built up. Land covered by buildings and other man-made structures.</li> <li>60: Bare / sparse vegetation. Lands with exposed soil, sand, or rocks and never has more than 10 % vegetated cover during any time of the year.</li> <li>70: Snow and ice. Lands under snow or ice cover throughout the year.</li> <li>80: Permanent water bodies. Lakes, reservoirs, and rivers. Can be either fresh or salt-water bodies.</li> <li>90: Herbaceous wetland. Lands with a permanent mixture of water and herbaceous or woody vegetation. The vegetation can be present in either salt, brackish, or fresh water.</li> <li>100: Moss and lichen.</li> <li>111: Closed forest, evergreen needle leaf. Tree canopy >70 %, almost all needle leaf trees remain green all year. Canopy is never without green foliage.</li> <li>112: Closed forest, evergreen broad leaf. Tree canopy >70 %, almost all broadleaf trees remain green year round. Canopy is never without green foliage.</li> <li>113: Closed forest, deciduous needle leaf. Tree canopy >70 %, consists of seasonal needle leaf tree communities with an annual cycle of leaf-on and leaf-off periods.</li> <li>114: Closed forest, deciduous broad leaf. Tree canopy >70 %, consists of seasonal broadleaf tree communities with an annual cycle of leaf-on and leaf-off periods.</li> <li>115: Closed forest, mixed.</li> <li>116: Closed forest, not matching any of the other definitions.</li> <li>121: Open forest, evergreen needle leaf. Top layer- trees 15-70 % and second layer- mixed of shrubs and grassland, almost all needle leaf trees remain green all year. Canopy is never without green foliage.</li> <li>122:Open forest, evergreen broad leaf. Top layer- trees 15-70 % and second layer- mixed of shrubs and grassland, almost all broadleaf trees remain green year round. Canopy is never without green foliage.</li> <li>123: Open forest, deciduous needle leaf. Top layer- trees 15-70 % and second layer- mixed of shrubs and grassland, consists of seasonal needle leaf tree communities with an annual cycle of leaf-on and leaf-off periods.</li> <li>124: Open forest, deciduous broad leaf. Top layer- trees 15-70 % and second layer- mixed of shrubs and grassland, consists of seasonal broadleaf tree communities with an annual cycle of leaf-on and leaf-off periods.</li> <li>125: Open forest, mixed.</li> <li>126: Open forest, not matching any of the other definitions.</li> <li>200: Oceans, seas. Can be either fresh or salt-water bodies.</li> </ul> <p>Forest type legend:</p> <ul> <li>0: Unknown</li> <li>1: Evergreen needle leaf</li> <li>2: Evergreen broad leaf</li> <li>3: Deciduous needle leaf</li> <li>4: Deciduous broad leaf</li> <li>5: Mix of forest types</li> </ul> <p>More detail on the classification algorithm and the resulting maps can be found in the accompanying paper: </p> <p>Souverijns, N.; Buchhorn, M.; Horion, S.; Fensholt, R.; Verbeeck, H.; Verbesselt, J.; Herold, M.; Tsendbazar, N.-E.; Bernardino, P.N.; Somers, B.; Van De Kerchove, R. Thirty Years of Land Cover and Fraction Cover Changes over the Sudano-Sahel Using Landsat Time Series. <em>Remote Sens.</em> <strong>2020</strong>, <em>12</em>, 3817. https://doi.org/10.3390/rs12223817</p> <p>Please note that a quality layer is available for each of the historical areas / periods (Landsat_LC30_epochYYYY_AREA_DataDensityIndicator.tif). In case a value of 4 or lower is achieved here, the discrete land cover classification / cover fraction for this period / area is highly uncertain. Take this into account when analysing the maps. Furthermore, take note that there is a large difference between the temporally cleaned (Landsat_LC30_epochYYYY_AREA_discrete-classification-HMM.tif) and original discrete land cover classification (Landsat_LC30_epochYYYY_AREA_discrete-classification.tif). We recommend to use the temporally cleaned version in combination with the quality layer.</p>
Sahel Land Cover OSO 2018
<p>A land cover map of the Sahel region for the reference year 2018 produced by supervised classification of Sentinel-2 image time series and using the <a href="https://land.copernicus.eu/global/products/lc">CGLS</a> maps as reference data for supervision.</p> <p>The nomenclature is the following:</p> <p>tree cover:10<br> forest:100<br> evergreen needleleaf closed forest:111<br> evergreen broadleaf closed forest:112<br> deciduous needleleaf closed forest:113<br> deciduous broadleaf closed forest:114<br> closed forest mixed:115<br> closed forest unknown type:116<br> evergreen needleleaf open forest:121<br> evergreen broadleaf open forest:122<br> deciduous needleleaf open forest:123<br> deciduous broadleaf open forest:124<br> open forest mixed:125<br> open forest unknown type:126<br> shrubs:20<br> herbaceous vegetation:30<br> cropland:40<br> urban:50<br> bare / sparse vegetation:60<br> snow & ice:70<br> permanent water bodies:80<br> temporary water bodies:81<br> herbaceous wetland:90<br> sea:200<br> continental land mass not classified:255</p> <p>The map was produced using <a href="http://iota2.net">iota2</a>, a free and open source platform for automatic map production using satellite image time series.</p>
Data from: Tracing the origin of the early wet-season Anopheles coluzzii in the Sahel
In arid environments the source of the malaria mosquito populations that re-establish soon after first rains remains a puzzle and alternative explanations have been proposed. Using genetic data, we evaluated whether the early Rainy Season (RS) population of Anopheles coluzzii is descended from the preceding late-RS generation at the same locality, consistent with dry season (DS) dormancy (aestivation), or from migrants from distant locations. Distinct predictions derived from these two hypotheses were assessed, based on variation in 738 SNPs in eleven A. coluzzii samples, including seven samples spanning two years in a Sahelian village. As predicted by the 'local origin under aestivation hypothesis', temporal samples from the late RS and those collected after the first rain of the following RS were clustered together, whilst larger genetic distances were found among samples spanning the RS. Likewise, multi-locus genotype composition of samples from the end of the RS were similar across samples until the following RS, unlike samples that spanned the RS. Consistent with reproductive arrest during the DS, no genetic drift was detected between samples taken over that period, despite encompassing extreme population minima, whereas it was detected between samples spanning the RS. Accordingly, the variance in allele frequency increased with time over the RS, but not over the DS. However, not all the results agreed with aestivation. Large genetic distances separated samples taken a year apart, and during the first year, within-sample genetic diversity declined and increased back during the late RS, suggesting a bottleneck followed by migration. The decline of genetic diversity followed a mass distribution of insecticide treated nets was accompanied by a reduced mosquito density and a rise in the mutation conferring resistance to pyrethroids, indicating a bottleneck due to insecticidal selection. Overall, our results support aestivation in A. coluzzii during the DS that is accompanied by long distance migration in the late-RS.
Distribution. Confirmed from NW Africa, the Sahel, and Nile Valley, E through the Middle East and WArabia to NW& C India (E to E Madhya Pradesh, 80° E); with possible distribution spots in E & SE India (indicated byfour mostlyhistorical records). Reportedly common in Bangladesh (yet disproved by recent reports) and retained on species lists of Myanmar, Thailand, and Sumatra without being supported by anyrecent record. in Rhinopomatidae
Distribution. Confirmed from NW Africa, the Sahel, and Nile Valley, E through the Middle East and WArabia to NW& C India (E to E Madhya Pradesh, 80° E); with possible distribution spots in E & SE India (indicated byfour mostlyhistorical records). Reportedly common in Bangladesh (yet disproved by recent reports) and retained on species lists of Myanmar, Thailand, and Sumatra without being supported by anyrecent record.
Subspecies and Distribution. L.v.victoriaeThomas,1893—Tanzania. L.v.angolensisThomas,1904—Angola. L.v.senegalensisRochebrune,1883—Senegal,TheGambia. L. v. whyte: Thomas, 1894 — Malawi. The African Savanna Hare is present from the Atlantic coast of NW Africa (Western Sahara S to Guinea), E across the Sahel to Sudan and the extreme W Ethiopia, S through E Africa (E DR Congo, Uganda, W Kenya, Rwanda, Burundi, and Tanzania) to most of Angola, Zambia, Malawi, NE Namibia, Botswana, Zimbabwe, Mozambique, E South Africa, Swaziland, and Lesotho; a small isolated population exists near Beni Abbas in the Sahara Desert in W Algeria. in Leporidae
Subspecies and Distribution. L.v.victoriaeThomas,1893—Tanzania. L.v.angolensisThomas,1904—Angola. L.v.senegalensisRochebrune,1883—Senegal,TheGambia. L. v. whyte: Thomas, 1894 — Malawi. The African Savanna Hare is present from the Atlantic coast of NW Africa (Western Sahara S to Guinea), E across the Sahel to Sudan and the extreme W Ethiopia, S through E Africa (E DR Congo, Uganda, W Kenya, Rwanda, Burundi, and Tanzania) to most of Angola, Zambia, Malawi, NE Namibia, Botswana, Zimbabwe, Mozambique, E South Africa, Swaziland, and Lesotho; a small isolated population exists near Beni Abbas in the Sahara Desert in W Algeria.
Quantitatively Monitoring the Resilience of Patterned Vegetation in the Sahel
Processed monthly Sentinel-2 image data for 42 patterned vegetation sites across the Sahel. Data includes RGB images, greyscale NDVI images and binary BWNDVI sub-images. These sub-images contain black pixels for vegetation and white pixels for soil, with 289 sub-images corresponding to a single image. Sentinel images are provided by Copernicus and accessed via Google Earth Engine.
Data from: WRF 1960-2014 winter season simulations of particulate matter in the Sahel: implications for air quality and respiratory health
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Data from: Tracing the origin of the early wet-season Anopheles coluzzii in the Sahel
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